CloudRaker gives teams one place to get paperwork done. AI handles the repetitive work, rules guide what happens, and teams stay in control.
Documents, emails, and forms land in one workspace. CloudRaker extracts the facts, shows source spans, and asks for review only where confidence or policy requires it.
Template looks good
Each workflow carries field rules, approvals, naming conventions, and the exact handoffs your team normally keeps in their heads.
The model can draft and recommend. It cannot write to the system of record until the paperwork agent checks permissions, required fields, and human approval gates.
Draft approved by Legal
Signature packet issued
Hash recorded on evidence log
Source material, model output, user review, and final action are recorded together so audit is not a separate cleanup project.
CloudRaker found page 6 and attached the source.
Ready for approval after clause update.
Approve with noteOperators, reviewers, and agents work on the same run instead of forwarding screenshots, spreadsheets, and ticket updates between teams.
Teams can see what is queued, blocked, approved, and shipped across every paperwork agent without asking where the work went.
Everything you build on CloudRaker can be invoked anywhere. Bring capabilities, automations, and knowledge into your applications, systems, AI agents, and workplace tools through REST API and MCP.
Build once. Run across your enterprise.
CloudRaker separates reasoning from authority. Models help with reading, drafting, and recommendations; deterministic controls decide what can execute.
The agent turns raw material into structured intent: extracted fields, suggested next steps, draft messages, and missing-information flags.
Schema rules, policy checks, permissions, and required approvals run before anything leaves the workspace.
Reviewers see the evidence, the recommendation, and the reason a decision is needed. Routine work keeps moving; risky work slows down.
Only validated actions reach downstream systems. Each write, notification, and generated document carries an audit trail.
The product covers the baseline work required to put AI into production workflows, not just a demo environment.
The product is the run itself: facts, people, model output, controls, and system actions in one operational record.
Same capabilities underneath. Pick whichever surface fits how you work.
Send us a real intake, submission, packet, or case opening. We will show how CloudRaker reads it, builds the run, asks for approvals, and produces the proof trail.
Amelia flagged the renewal notice.